{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multi-layer FNN on MNIST\n",
    "\n",
    "This is MLP (784-X^W-10) on MNIST. SGD algorithm (lr=0.1) with 100 epoches.\n",
    "\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os, sys\n",
    "import numpy as np\n",
    "from matplotlib.pyplot import *\n",
    "import locale\n",
    "locale.setlocale(locale.LC_ALL, 'en_US.UTF-8')\n",
    "\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.font_manager as font_manager\n",
    "import seaborn as sns\n",
    "import itertools\n",
    "import scipy.io as sio\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "depth = [1,2,3,4,5]\n",
    "width = [50,100,200,400]\n",
    "data = sio.loadmat('data_optimizer_cmp/fnn_mnist_all_sgd_local.mat')\n",
    "\n",
    "acc_test_all   = data['acc_solved_all'] \n",
    "num_param_all  = data['num_param_all'] \n",
    "dim_solved_all = data['dim_solved_all'] \n",
    "acc_solved_all = data['acc_solved_all'] \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baseline results\n",
      "[[ 0.8808  0.8748  0.8797  0.1066  0.1473]\n",
      " [ 0.8845  0.884   0.8851  0.8829  0.8852]\n",
      " [ 0.8862  0.8982  0.8879  0.8884  0.8922]\n",
      " [ 0.8859  0.8913  0.8871  0.8903  0.8875]]\n",
      "# Parmas\n",
      "[[  39760.   42310.   44860.   47410.   49960.]\n",
      " [  79510.   89610.   99710.  109810.  119910.]\n",
      " [ 159010.  199210.  239410.  279610.  319810.]\n",
      " [ 318010.  478410.  638810.  799210.  959610.]]\n",
      "Cross-line results\n",
      "[[ 0.8808  0.8748  0.8797  0.1066  0.1473]\n",
      " [ 0.8845  0.884   0.8851  0.8829  0.8852]\n",
      " [ 0.8862  0.8982  0.8879  0.8884  0.8922]\n",
      " [ 0.8859  0.8913  0.8871  0.8903  0.8875]]\n",
      "Cross-line Dim\n",
      "[[ 475.  425.  450.   10.   10.]\n",
      " [ 525.  500.  500.  500.  475.]\n",
      " [ 550.  550.  500.  550.  575.]\n",
      " [ 550.  600.  575.  575.  575.]]\n"
     ]
    }
   ],
   "source": [
    "print \"Baseline results\"\n",
    "print acc_test_all\n",
    "\n",
    "print \"# Parmas\"\n",
    "print num_param_all\n",
    "\n",
    "print \"Cross-line results\"\n",
    "print acc_solved_all\n",
    "\n",
    "print \"Cross-line Dim\"\n",
    "print dim_solved_all\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### List the config of depth and width, which yields errors in training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error in the following configs: width, depth and dim\n",
      "[]\n",
      "[]\n",
      "[]\n",
      "Shape of accuracy tensor: (1, 1, 32)\n",
      "[ 0.11356  0.1169   0.22276  0.32912  0.42362  0.50796  0.59456  0.68228\n",
      "  0.74778  0.7934   0.8173   0.84238  0.847    0.85462  0.8422   0.1092\n",
      "  0.10796  0.10698  0.10658  0.10546  0.10534  0.1054   0.10634  0.10576\n",
      "  0.10468  0.10436  0.10384  0.10286  0.10264  0.10276  0.1032   0.10328]\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check the accuracy of specific depth and width, along different dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reshape the tensor to 1D for plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Testing Accuracy wrt. Width, Depth and Dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Testing Accuracy of Intrinsic dim for #parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Intrinsic dim for #parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA4wAAAFQCAYAAAD0qfDfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1589990c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,5))\n",
    "\n",
    "font = {'family' : 'normal',\n",
    "        'weight' : 'normal',\n",
    "        'size'   : 16}\n",
    "matplotlib.rc('font', **font)\n",
    "\n",
    "\n",
    "\n",
    "data = sio.loadmat('data_optimizer_cmp/fnn_mnist_all_sgd_local.mat')\n",
    "num_param_all  = data['num_param_all']\n",
    "dim_solved_all = data['dim_solved_all']\n",
    "fig_params_1d = num_param_all.reshape(len(depth)*len(width),order='F')\n",
    "dim_solved_all_1d = dim_solved_all.reshape(len(depth)*len(width),order='F')\n",
    "\n",
    "plt.scatter(fig_params_1d, dim_solved_all_1d, s=(np.array(fig_width)**2.0)/100, c=fig_depth, alpha=0.1, edgecolors='k') \n",
    "\n",
    "\n",
    "data = sio.loadmat('data_optimizer_cmp/fnn_mnist_all_adam_local.mat')\n",
    "num_param_all  = data['num_param_all']\n",
    "dim_solved_all = data['dim_solved_all']\n",
    "fig_params_1d = num_param_all.reshape(len(depth)*len(width),order='F')\n",
    "dim_solved_all_1d = dim_solved_all.reshape(len(depth)*len(width),order='F')\n",
    "\n",
    "plt.scatter(fig_params_1d, dim_solved_all_1d, s=(np.array(fig_width)**2.0)/100, c=fig_depth, edgecolors='k') \n",
    "\n",
    "ax = plt.gca()\n",
    "cbar = plt.colorbar(label=\"Depth\")\n",
    "from matplotlib.ticker import MaxNLocator\n",
    "\n",
    "# arange(12)\n",
    "# cbar.ax.yaxis.set_major_locator(MaxNLocator(nbins=5,integer=True))\n",
    "\n",
    "\n",
    "ax.set_xscale('log')\n",
    "ax.grid(True)\n",
    "ax.set_ylim(400, 1000)\n",
    "\n",
    "plt.xlabel('# Model parameters')\n",
    "plt.ylabel('Intrinsic dim $d_{int}$')\n",
    "ax.set_xlim(0.3E5, 1.5E6)\n",
    "\n",
    "#make a legend:\n",
    "pws = width\n",
    "for pw in pws:\n",
    "    plt.scatter([], [], s=(pw**1.8)/100, c=\"k\",label=str(pw))\n",
    "\n",
    "h, l = plt.gca().get_legend_handles_labels()\n",
    "plt.legend(h[0:], l[0:], labelspacing=1.2, title=\"layer width\", borderpad=1, \n",
    "            frameon=True, framealpha=0.6, edgecolor=\"k\", facecolor=\"w\",loc='best')\n",
    "\n",
    "fig.savefig(\"figs/fnn_mnist_local_optimizer_cmp.pdf\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performance comparison with Baseline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA4wAAAFQCAYAAAD0qfDfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZJqMmGUJEmSJNVkwihJkiRJqun/A803Nf4bceEzAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1588f4c2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,5))\n",
    "\n",
    "font = {'family' : 'normal',\n",
    "        'weight' : 'normal',\n",
    "        'size'   : 16}\n",
    "matplotlib.rc('font', **font)\n",
    "\n",
    "\n",
    "\n",
    "data = sio.loadmat('data_optimizer_cmp/fnn_mnist_all_sgd_global.mat')\n",
    "num_param_all  = data['num_param_all']\n",
    "dim_solved_all = data['dim_solved_all']\n",
    "fig_params_1d = num_param_all.reshape(len(depth)*len(width),order='F')\n",
    "dim_solved_all_1d = dim_solved_all.reshape(len(depth)*len(width),order='F')\n",
    "\n",
    "plt.scatter(fig_params_1d, dim_solved_all_1d, s=(np.array(fig_width)**2.0)/100, c=fig_depth, alpha=0.2, edgecolors='k') \n",
    "\n",
    "\n",
    "data = sio.loadmat('data_optimizer_cmp/fnn_mnist_all_adam_global.mat')\n",
    "num_param_all  = data['num_param_all']\n",
    "dim_solved_all = data['dim_solved_all']\n",
    "fig_params_1d = num_param_all.reshape(len(depth)*len(width),order='F')\n",
    "dim_solved_all_1d = dim_solved_all.reshape(len(depth)*len(width),order='F')\n",
    "\n",
    "plt.scatter(fig_params_1d, dim_solved_all_1d, s=(np.array(fig_width)**2.0)/100, c=fig_depth, edgecolors='k') \n",
    "\n",
    "\n",
    "ax = plt.gca()\n",
    "plt.colorbar(label=\"Depth\")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "ax.grid(True)\n",
    "ax.set_ylim(400, 1000)\n",
    "\n",
    "plt.xlabel('# Model parameters')\n",
    "plt.ylabel('Intrinsic dim $d_{int}$')\n",
    "ax.set_xlim(0.3E5, 1.5E6)\n",
    "\n",
    "#make a legend:\n",
    "# pws = width\n",
    "# for pw in pws:\n",
    "#     plt.scatter([], [], s=(pw**1.8)/100, c=\"k\",label=str(pw))\n",
    "\n",
    "# h, l = plt.gca().get_legend_handles_labels()\n",
    "# plt.legend(h[0:], l[0:], labelspacing=1.2, title=\"layer width\", borderpad=1, \n",
    "#             frameon=True, framealpha=0.6, edgecolor=\"k\", facecolor=\"w\",loc='best')\n",
    "\n",
    "fig.savefig(\"figs/fnn_mnist_global_optimizer_cmp.pdf\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
